FA-79186 / Image orientation metadata / Open access
Transverse canvas translation swaps its offsets · case 01
Tag-7 photos are shifted out of the canvas when width and height differ.
ROOT CAUSE
The x offset must be the stored height and the y offset the stored width; they are exchanged.
VERIFIED REPAIR
Use e = h and f = w for tag 7.
Unsuccessful approach: Dropping the negations turns the transverse into a translated transpose.
Case contract
Input [w, h, tag]. Produce the canvas size and the 2D affine [a, b, c, d, e, f] (x' = a*x + c*y + e, y' = b*x + d*y + f, continuous coordinates, so mirroring an extent e maps x to e - x) that draws the stored image upright. Tags 5..8 use a [h, w] canvas; invalid tags are treated as 1.
Why this case matters
Camera, phone and scanner images carry an orientation hint separately from the stored pixels; galleries, thumbnailers, editors and upload pipelines must interpret it consistently or photos appear sideways, mirrored or doubly rotated.
1 / The failure
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(x):
w, h, tag = x
if tag not in (1, 2, 3, 4, 5, 6, 7, 8):
tag = 1
if tag == 1:
mat = [1, 0, 0, 1, 0, 0]
elif tag == 2:
mat = [-1, 0, 0, 1, w, 0]
elif tag == 3:
mat = [-1, 0, 0, -1, w, h]
elif tag == 4:
mat = [1, 0, 0, -1, 0, h]
elif tag == 5:
mat = [0, 1, 1, 0, 0, 0]
elif tag == 6:
mat = [0, 1, -1, 0, h, 0]
elif tag == 7:
mat = [0, -1, -1, 0, w, h]
else:
mat = [0, -1, 1, 0, 0, w]
canvas = [h, w] if tag >= 5 else [w, h]
return {'canvas': canvas, 'matrix': mat}
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[[[1105, 1652, 7], {'canvas': [1652, 1105], 'matrix': [0, -1, -1, 0, 1652, 1105]}], [[2606, 861, 7], {'canvas': [861, 2606], 'matrix': [0, -1, -1, 0, 861, 2606]}], [[3307, 2787, 3], {'canvas': [3307, 2787], 'matrix': [-1, 0, 0, -1, 3307, 2787]}], [[2954, 1709, 1], {'canvas': [2954, 1709], 'matrix': [1, 0, 0, 1, 0, 0]}], [[58, 1879, 3], {'canvas': [58, 1879], 'matrix': [-1, 0, 0, -1, 58, 1879]}], [[2834, 740, 9], {'canvas': [2834, 740], 'matrix': [1, 0, 0, 1, 0, 0]}], [[1990, 1071, 4], {'canvas': [1990, 1071], 'matrix': [1, 0, 0, -1, 0, 1071]}], [[2907, 3052, 7], {'canvas': [3052, 2907], 'matrix': [0, -1, -1, 0, 3052, 2907]}]], [[[3503, 2694, 7], {'canvas': [2694, 3503], 'matrix': [0, -1, -1, 0, 2694, 3503]}], [[1061, 3711, 7], {'canvas': [3711, 1061], 'matrix': [0, -1, -1, 0, 3711, 1061]}], [[2349, 3183, 4], {'canvas': [2349, 3183], 'matrix': [1, 0, 0, -1, 0, 3183]}], [[1404, 638, 8], {'canvas': [638, 1404], 'matrix': [0, -1, 1, 0, 0, 1404]}], [[497, 2889, 6], {'canvas': [2889, 497], 'matrix': [0, 1, -1, 0, 2889, 0]}], [[1679, 3857, 0], {'canvas': [1679, 3857], 'matrix': [1, 0, 0, 1, 0, 0]}], [[1194, 3699, 6], {'canvas': [3699, 1194], 'matrix': [0, 1, -1, 0, 3699, 0]}], [[3671, 3387, 7], {'canvas': [3387, 3671], 'matrix': [0, -1, -1, 0, 3387, 3671]}]], [[[1938, 383, 7], {'canvas': [383, 1938], 'matrix': [0, -1, -1, 0, 383, 1938]}], [[896, 2598, 7], {'canvas': [2598, 896], 'matrix': [0, -1, -1, 0, 2598, 896]}], [[1742, 3974, 6], {'canvas': [3974, 1742], 'matrix': [0, 1, -1, 0, 3974, 0]}], [[2878, 1614, 0], {'canvas': [2878, 1614], 'matrix': [1, 0, 0, 1, 0, 0]}], [[1553, 978, 5], {'canvas': [978, 1553], 'matrix': [0, 1, 1, 0, 0, 0]}], [[2394, 1311, 0], {'canvas': [2394, 1311], 'matrix': [1, 0, 0, 1, 0, 0]}], [[1506, 1188, 8], {'canvas': [1188, 1506], 'matrix': [0, -1, 1, 0, 0, 1506]}], [[3706, 2370, 7], {'canvas': [2370, 3706], 'matrix': [0, -1, -1, 0, 2370, 3706]}]], [[[474, 234, 7], {'canvas': [234, 474], 'matrix': [0, -1, -1, 0, 234, 474]}], [[295, 2120, 7], {'canvas': [2120, 295], 'matrix': [0, -1, -1, 0, 2120, 295]}], [[1728, 2634, 3], {'canvas': [1728, 2634], 'matrix': [-1, 0, 0, -1, 1728, 2634]}], [[2618, 2128, 9], {'canvas': [2618, 2128], 'matrix': [1, 0, 0, 1, 0, 0]}], [[2422, 1413, 3], {'canvas': [2422, 1413], 'matrix': [-1, 0, 0, -1, 2422, 1413]}], [[397, 3269, 8], {'canvas': [3269, 397], 'matrix': [0, -1, 1, 0, 0, 397]}], [[1888, 3423, 4], {'canvas': [1888, 3423], 'matrix': [1, 0, 0, -1, 0, 3423]}], [[927, 1834, 7], {'canvas': [1834, 927], 'matrix': [0, -1, -1, 0, 1834, 927]}]], [[[66, 978, 7], {'canvas': [978, 66], 'matrix': [0, -1, -1, 0, 978, 66]}], [[610, 3719, 7], {'canvas': [3719, 610], 'matrix': [0, -1, -1, 0, 3719, 610]}], [[3666, 647, 2], {'canvas': [3666, 647], 'matrix': [-1, 0, 0, 1, 3666, 0]}], [[3653, 369, 3], {'canvas': [3653, 369], 'matrix': [-1, 0, 0, -1, 3653, 369]}], [[663, 894, 6], {'canvas': [894, 663], 'matrix': [0, 1, -1, 0, 894, 0]}], [[439, 1611, 8], {'canvas': [1611, 439], 'matrix': [0, -1, 1, 0, 0, 439]}], [[2083, 1309, 2], {'canvas': [2083, 1309], 'matrix': [-1, 0, 0, 1, 2083, 0]}], [[2448, 3969, 7], {'canvas': [3969, 2448], 'matrix': [0, -1, -1, 0, 3969, 2448]}]]]
labels = ["regression: tag 7 translation", "repair trap", "combined fault", "control", "control", "boundary", "boundary", "control"]
for i, (args, expected) in enumerate(fixtures[N-1]):
check("%s %d" % (labels[i % len(labels)], i), solve(args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
| Boundary fixture | Actual | Expected | Outcome |
|---|---|---|---|
| regression: tag 7 translation 0 | {'canvas': [1652, 1105], 'matrix': [0, -1, -1, 0, 1105, 1652]} | {'canvas': [1652, 1105], 'matrix': [0, -1, -1, 0, 1652, 1105]} | Failed |
| repair trap 1 | {'canvas': [861, 2606], 'matrix': [0, -1, -1, 0, 2606, 861]} | {'canvas': [861, 2606], 'matrix': [0, -1, -1, 0, 861, 2606]} | Failed |
| combined fault 2 | {'canvas': [3307, 2787], 'matrix': [-1, 0, 0, -1, 3307, 2787]} | {'canvas': [3307, 2787], 'matrix': [-1, 0, 0, -1, 3307, 2787]} | Passed |
| control 3 | {'canvas': [2954, 1709], 'matrix': [1, 0, 0, 1, 0, 0]} | {'canvas': [2954, 1709], 'matrix': [1, 0, 0, 1, 0, 0]} | Passed |
| control 4 | {'canvas': [58, 1879], 'matrix': [-1, 0, 0, -1, 58, 1879]} | {'canvas': [58, 1879], 'matrix': [-1, 0, 0, -1, 58, 1879]} | Passed |
| boundary 5 | {'canvas': [2834, 740], 'matrix': [1, 0, 0, 1, 0, 0]} | {'canvas': [2834, 740], 'matrix': [1, 0, 0, 1, 0, 0]} | Passed |
| boundary 6 | {'canvas': [1990, 1071], 'matrix': [1, 0, 0, -1, 0, 1071]} | {'canvas': [1990, 1071], 'matrix': [1, 0, 0, -1, 0, 1071]} | Passed |
| control 7 | {'canvas': [3052, 2907], 'matrix': [0, -1, -1, 0, 2907, 3052]} | {'canvas': [3052, 2907], 'matrix': [0, -1, -1, 0, 3052, 2907]} | Failed |
SHA-256 / fde317f6b979239530f277eafbb8a6eec7de24ee84f5f2aa0b54f0261583f82f
2 / The unsuccessful fix
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(x):
w, h, tag = x
if tag not in (1, 2, 3, 4, 5, 6, 7, 8):
tag = 1
if tag == 1:
mat = [1, 0, 0, 1, 0, 0]
elif tag == 2:
mat = [-1, 0, 0, 1, w, 0]
elif tag == 3:
mat = [-1, 0, 0, -1, w, h]
elif tag == 4:
mat = [1, 0, 0, -1, 0, h]
elif tag == 5:
mat = [0, 1, 1, 0, 0, 0]
elif tag == 6:
mat = [0, 1, -1, 0, h, 0]
elif tag == 7:
mat = [0, 1, 1, 0, h, w]
else:
mat = [0, -1, 1, 0, 0, w]
canvas = [h, w] if tag >= 5 else [w, h]
return {'canvas': canvas, 'matrix': mat}
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[[[1105, 1652, 7], {'canvas': [1652, 1105], 'matrix': [0, -1, -1, 0, 1652, 1105]}], [[2606, 861, 7], {'canvas': [861, 2606], 'matrix': [0, -1, -1, 0, 861, 2606]}], [[3307, 2787, 3], {'canvas': [3307, 2787], 'matrix': [-1, 0, 0, -1, 3307, 2787]}], [[2954, 1709, 1], {'canvas': [2954, 1709], 'matrix': [1, 0, 0, 1, 0, 0]}], [[58, 1879, 3], {'canvas': [58, 1879], 'matrix': [-1, 0, 0, -1, 58, 1879]}], [[2834, 740, 9], {'canvas': [2834, 740], 'matrix': [1, 0, 0, 1, 0, 0]}], [[1990, 1071, 4], {'canvas': [1990, 1071], 'matrix': [1, 0, 0, -1, 0, 1071]}], [[2907, 3052, 7], {'canvas': [3052, 2907], 'matrix': [0, -1, -1, 0, 3052, 2907]}]], [[[3503, 2694, 7], {'canvas': [2694, 3503], 'matrix': [0, -1, -1, 0, 2694, 3503]}], [[1061, 3711, 7], {'canvas': [3711, 1061], 'matrix': [0, -1, -1, 0, 3711, 1061]}], [[2349, 3183, 4], {'canvas': [2349, 3183], 'matrix': [1, 0, 0, -1, 0, 3183]}], [[1404, 638, 8], {'canvas': [638, 1404], 'matrix': [0, -1, 1, 0, 0, 1404]}], [[497, 2889, 6], {'canvas': [2889, 497], 'matrix': [0, 1, -1, 0, 2889, 0]}], [[1679, 3857, 0], {'canvas': [1679, 3857], 'matrix': [1, 0, 0, 1, 0, 0]}], [[1194, 3699, 6], {'canvas': [3699, 1194], 'matrix': [0, 1, -1, 0, 3699, 0]}], [[3671, 3387, 7], {'canvas': [3387, 3671], 'matrix': [0, -1, -1, 0, 3387, 3671]}]], [[[1938, 383, 7], {'canvas': [383, 1938], 'matrix': [0, -1, -1, 0, 383, 1938]}], [[896, 2598, 7], {'canvas': [2598, 896], 'matrix': [0, -1, -1, 0, 2598, 896]}], [[1742, 3974, 6], {'canvas': [3974, 1742], 'matrix': [0, 1, -1, 0, 3974, 0]}], [[2878, 1614, 0], {'canvas': [2878, 1614], 'matrix': [1, 0, 0, 1, 0, 0]}], [[1553, 978, 5], {'canvas': [978, 1553], 'matrix': [0, 1, 1, 0, 0, 0]}], [[2394, 1311, 0], {'canvas': [2394, 1311], 'matrix': [1, 0, 0, 1, 0, 0]}], [[1506, 1188, 8], {'canvas': [1188, 1506], 'matrix': [0, -1, 1, 0, 0, 1506]}], [[3706, 2370, 7], {'canvas': [2370, 3706], 'matrix': [0, -1, -1, 0, 2370, 3706]}]], [[[474, 234, 7], {'canvas': [234, 474], 'matrix': [0, -1, -1, 0, 234, 474]}], [[295, 2120, 7], {'canvas': [2120, 295], 'matrix': [0, -1, -1, 0, 2120, 295]}], [[1728, 2634, 3], {'canvas': [1728, 2634], 'matrix': [-1, 0, 0, -1, 1728, 2634]}], [[2618, 2128, 9], {'canvas': [2618, 2128], 'matrix': [1, 0, 0, 1, 0, 0]}], [[2422, 1413, 3], {'canvas': [2422, 1413], 'matrix': [-1, 0, 0, -1, 2422, 1413]}], [[397, 3269, 8], {'canvas': [3269, 397], 'matrix': [0, -1, 1, 0, 0, 397]}], [[1888, 3423, 4], {'canvas': [1888, 3423], 'matrix': [1, 0, 0, -1, 0, 3423]}], [[927, 1834, 7], {'canvas': [1834, 927], 'matrix': [0, -1, -1, 0, 1834, 927]}]], [[[66, 978, 7], {'canvas': [978, 66], 'matrix': [0, -1, -1, 0, 978, 66]}], [[610, 3719, 7], {'canvas': [3719, 610], 'matrix': [0, -1, -1, 0, 3719, 610]}], [[3666, 647, 2], {'canvas': [3666, 647], 'matrix': [-1, 0, 0, 1, 3666, 0]}], [[3653, 369, 3], {'canvas': [3653, 369], 'matrix': [-1, 0, 0, -1, 3653, 369]}], [[663, 894, 6], {'canvas': [894, 663], 'matrix': [0, 1, -1, 0, 894, 0]}], [[439, 1611, 8], {'canvas': [1611, 439], 'matrix': [0, -1, 1, 0, 0, 439]}], [[2083, 1309, 2], {'canvas': [2083, 1309], 'matrix': [-1, 0, 0, 1, 2083, 0]}], [[2448, 3969, 7], {'canvas': [3969, 2448], 'matrix': [0, -1, -1, 0, 3969, 2448]}]]]
labels = ["regression: tag 7 translation", "repair trap", "combined fault", "control", "control", "boundary", "boundary", "control"]
for i, (args, expected) in enumerate(fixtures[N-1]):
check("%s %d" % (labels[i % len(labels)], i), solve(args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
| Boundary fixture | Actual | Expected | Outcome |
|---|---|---|---|
| regression: tag 7 translation 0 | {'canvas': [1652, 1105], 'matrix': [0, 1, 1, 0, 1652, 1105]} | {'canvas': [1652, 1105], 'matrix': [0, -1, -1, 0, 1652, 1105]} | Failed |
| repair trap 1 | {'canvas': [861, 2606], 'matrix': [0, 1, 1, 0, 861, 2606]} | {'canvas': [861, 2606], 'matrix': [0, -1, -1, 0, 861, 2606]} | Failed |
| combined fault 2 | {'canvas': [3307, 2787], 'matrix': [-1, 0, 0, -1, 3307, 2787]} | {'canvas': [3307, 2787], 'matrix': [-1, 0, 0, -1, 3307, 2787]} | Passed |
| control 3 | {'canvas': [2954, 1709], 'matrix': [1, 0, 0, 1, 0, 0]} | {'canvas': [2954, 1709], 'matrix': [1, 0, 0, 1, 0, 0]} | Passed |
| control 4 | {'canvas': [58, 1879], 'matrix': [-1, 0, 0, -1, 58, 1879]} | {'canvas': [58, 1879], 'matrix': [-1, 0, 0, -1, 58, 1879]} | Passed |
| boundary 5 | {'canvas': [2834, 740], 'matrix': [1, 0, 0, 1, 0, 0]} | {'canvas': [2834, 740], 'matrix': [1, 0, 0, 1, 0, 0]} | Passed |
| boundary 6 | {'canvas': [1990, 1071], 'matrix': [1, 0, 0, -1, 0, 1071]} | {'canvas': [1990, 1071], 'matrix': [1, 0, 0, -1, 0, 1071]} | Passed |
| control 7 | {'canvas': [3052, 2907], 'matrix': [0, 1, 1, 0, 3052, 2907]} | {'canvas': [3052, 2907], 'matrix': [0, -1, -1, 0, 3052, 2907]} | Failed |
SHA-256 / 937dac00b6c9a8cf03bbae56eb96afe2721610efc5fb4d08937ac87da7c889a1
3 / The verified repair
Exit 0"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(x):
w, h, tag = x
if tag not in (1, 2, 3, 4, 5, 6, 7, 8):
tag = 1
if tag == 1:
mat = [1, 0, 0, 1, 0, 0]
elif tag == 2:
mat = [-1, 0, 0, 1, w, 0]
elif tag == 3:
mat = [-1, 0, 0, -1, w, h]
elif tag == 4:
mat = [1, 0, 0, -1, 0, h]
elif tag == 5:
mat = [0, 1, 1, 0, 0, 0]
elif tag == 6:
mat = [0, 1, -1, 0, h, 0]
elif tag == 7:
mat = [0, -1, -1, 0, h, w]
else:
mat = [0, -1, 1, 0, 0, w]
canvas = [h, w] if tag >= 5 else [w, h]
return {'canvas': canvas, 'matrix': mat}
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[[[1105, 1652, 7], {'canvas': [1652, 1105], 'matrix': [0, -1, -1, 0, 1652, 1105]}], [[2606, 861, 7], {'canvas': [861, 2606], 'matrix': [0, -1, -1, 0, 861, 2606]}], [[3307, 2787, 3], {'canvas': [3307, 2787], 'matrix': [-1, 0, 0, -1, 3307, 2787]}], [[2954, 1709, 1], {'canvas': [2954, 1709], 'matrix': [1, 0, 0, 1, 0, 0]}], [[58, 1879, 3], {'canvas': [58, 1879], 'matrix': [-1, 0, 0, -1, 58, 1879]}], [[2834, 740, 9], {'canvas': [2834, 740], 'matrix': [1, 0, 0, 1, 0, 0]}], [[1990, 1071, 4], {'canvas': [1990, 1071], 'matrix': [1, 0, 0, -1, 0, 1071]}], [[2907, 3052, 7], {'canvas': [3052, 2907], 'matrix': [0, -1, -1, 0, 3052, 2907]}]], [[[3503, 2694, 7], {'canvas': [2694, 3503], 'matrix': [0, -1, -1, 0, 2694, 3503]}], [[1061, 3711, 7], {'canvas': [3711, 1061], 'matrix': [0, -1, -1, 0, 3711, 1061]}], [[2349, 3183, 4], {'canvas': [2349, 3183], 'matrix': [1, 0, 0, -1, 0, 3183]}], [[1404, 638, 8], {'canvas': [638, 1404], 'matrix': [0, -1, 1, 0, 0, 1404]}], [[497, 2889, 6], {'canvas': [2889, 497], 'matrix': [0, 1, -1, 0, 2889, 0]}], [[1679, 3857, 0], {'canvas': [1679, 3857], 'matrix': [1, 0, 0, 1, 0, 0]}], [[1194, 3699, 6], {'canvas': [3699, 1194], 'matrix': [0, 1, -1, 0, 3699, 0]}], [[3671, 3387, 7], {'canvas': [3387, 3671], 'matrix': [0, -1, -1, 0, 3387, 3671]}]], [[[1938, 383, 7], {'canvas': [383, 1938], 'matrix': [0, -1, -1, 0, 383, 1938]}], [[896, 2598, 7], {'canvas': [2598, 896], 'matrix': [0, -1, -1, 0, 2598, 896]}], [[1742, 3974, 6], {'canvas': [3974, 1742], 'matrix': [0, 1, -1, 0, 3974, 0]}], [[2878, 1614, 0], {'canvas': [2878, 1614], 'matrix': [1, 0, 0, 1, 0, 0]}], [[1553, 978, 5], {'canvas': [978, 1553], 'matrix': [0, 1, 1, 0, 0, 0]}], [[2394, 1311, 0], {'canvas': [2394, 1311], 'matrix': [1, 0, 0, 1, 0, 0]}], [[1506, 1188, 8], {'canvas': [1188, 1506], 'matrix': [0, -1, 1, 0, 0, 1506]}], [[3706, 2370, 7], {'canvas': [2370, 3706], 'matrix': [0, -1, -1, 0, 2370, 3706]}]], [[[474, 234, 7], {'canvas': [234, 474], 'matrix': [0, -1, -1, 0, 234, 474]}], [[295, 2120, 7], {'canvas': [2120, 295], 'matrix': [0, -1, -1, 0, 2120, 295]}], [[1728, 2634, 3], {'canvas': [1728, 2634], 'matrix': [-1, 0, 0, -1, 1728, 2634]}], [[2618, 2128, 9], {'canvas': [2618, 2128], 'matrix': [1, 0, 0, 1, 0, 0]}], [[2422, 1413, 3], {'canvas': [2422, 1413], 'matrix': [-1, 0, 0, -1, 2422, 1413]}], [[397, 3269, 8], {'canvas': [3269, 397], 'matrix': [0, -1, 1, 0, 0, 397]}], [[1888, 3423, 4], {'canvas': [1888, 3423], 'matrix': [1, 0, 0, -1, 0, 3423]}], [[927, 1834, 7], {'canvas': [1834, 927], 'matrix': [0, -1, -1, 0, 1834, 927]}]], [[[66, 978, 7], {'canvas': [978, 66], 'matrix': [0, -1, -1, 0, 978, 66]}], [[610, 3719, 7], {'canvas': [3719, 610], 'matrix': [0, -1, -1, 0, 3719, 610]}], [[3666, 647, 2], {'canvas': [3666, 647], 'matrix': [-1, 0, 0, 1, 3666, 0]}], [[3653, 369, 3], {'canvas': [3653, 369], 'matrix': [-1, 0, 0, -1, 3653, 369]}], [[663, 894, 6], {'canvas': [894, 663], 'matrix': [0, 1, -1, 0, 894, 0]}], [[439, 1611, 8], {'canvas': [1611, 439], 'matrix': [0, -1, 1, 0, 0, 439]}], [[2083, 1309, 2], {'canvas': [2083, 1309], 'matrix': [-1, 0, 0, 1, 2083, 0]}], [[2448, 3969, 7], {'canvas': [3969, 2448], 'matrix': [0, -1, -1, 0, 3969, 2448]}]]]
labels = ["regression: tag 7 translation", "repair trap", "combined fault", "control", "control", "boundary", "boundary", "control"]
for i, (args, expected) in enumerate(fixtures[N-1]):
check("%s %d" % (labels[i % len(labels)], i), solve(args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
| Boundary fixture | Actual | Expected | Outcome |
|---|---|---|---|
| regression: tag 7 translation 0 | {'canvas': [1652, 1105], 'matrix': [0, -1, -1, 0, 1652, 1105]} | {'canvas': [1652, 1105], 'matrix': [0, -1, -1, 0, 1652, 1105]} | Passed |
| repair trap 1 | {'canvas': [861, 2606], 'matrix': [0, -1, -1, 0, 861, 2606]} | {'canvas': [861, 2606], 'matrix': [0, -1, -1, 0, 861, 2606]} | Passed |
| combined fault 2 | {'canvas': [3307, 2787], 'matrix': [-1, 0, 0, -1, 3307, 2787]} | {'canvas': [3307, 2787], 'matrix': [-1, 0, 0, -1, 3307, 2787]} | Passed |
| control 3 | {'canvas': [2954, 1709], 'matrix': [1, 0, 0, 1, 0, 0]} | {'canvas': [2954, 1709], 'matrix': [1, 0, 0, 1, 0, 0]} | Passed |
| control 4 | {'canvas': [58, 1879], 'matrix': [-1, 0, 0, -1, 58, 1879]} | {'canvas': [58, 1879], 'matrix': [-1, 0, 0, -1, 58, 1879]} | Passed |
| boundary 5 | {'canvas': [2834, 740], 'matrix': [1, 0, 0, 1, 0, 0]} | {'canvas': [2834, 740], 'matrix': [1, 0, 0, 1, 0, 0]} | Passed |
| boundary 6 | {'canvas': [1990, 1071], 'matrix': [1, 0, 0, -1, 0, 1071]} | {'canvas': [1990, 1071], 'matrix': [1, 0, 0, -1, 0, 1071]} | Passed |
| control 7 | {'canvas': [3052, 2907], 'matrix': [0, -1, -1, 0, 3052, 2907]} | {'canvas': [3052, 2907], 'matrix': [0, -1, -1, 0, 3052, 2907]} | Passed |
SHA-256 / 815a62342489b74a11e38cff9130e4bacdaf2fb5f282f94355efb6b133c54c6f
Verification & scope
A deterministic bounded teaching model with a stipulated contract; it makes no claim of conformance to any published specification. This reproducer isolates one failure mechanism. Results cover the supplied fixtures. Variants within a family share a test contract and should remain grouped when constructing evaluation splits. Related mechanisms with a shared evaluation_group must also remain together; these controlled models are not independent production incidents.
Observations recorded using Python 3.12.14 at 2026-09-29T14:49:42.400882+00:00.
Case digest / ff2b4390b837cfbe71865b26b19d53f68e27d58e27548ec1516d65791cfbb816